Validation

Validation of Pharmaceuticals

1. VALIDATION Presented by – Arif Nadaf M. Pharm (Pharmaceutics) Jamia Hamdard University, New Delhi

2. Validation means to Confirm, Establish, Authenticate or Define the Results Or Outcomes that are obtained from the work which is done. What is validation ?

3. Action of proving, in accordance with the GMP , that any Procedure, Process, Equipment, Material, Activity Or System actually leads to the expected results . Validation as per who / pics VALIDATION AS PER 21 CFR Validation means confirmation by examination and provision by objective evidence that the particular requirements for a specific intended use can be consistently fulfilled .

4. Process validation Equipment validation Facility validation HVAC system validation ( Heating, ventilation and air conditioning) Cleaning validation Analytical method validation Computer system validation Types of validation

5. Process validation is defined as the collection and evaluation of data, from the process design stage through commercial production, which establishes scientific evidence that a process is capable of consistently delivering quality product. Process validation :

6. Why process validation is required Weather your process is effectively controlling the quality of your finished product or not ?

7. Process design : The goal of this stage is to design a process suitable for routine commercial manufacturing that can consistently deliver a product that meets its quality attributes. Process qualification : The process design is evaluated to determine if it is capable of reproducible commercial manufacture: The stage has two elements: -design of facility and qualification of equipment and utilities. -Process Performance Qualification (PPQ) Continued process verification: The goal of this stage is continual assurance that the process remain in state of control (validated state) during commercial manufacturing. Evaluating the performance of process identifies problems and determines weather actions must be taken to correct, anticipate and prevent so that process remain in control. Stages of process validation:

8. Process validation:

9. Types of process validation:

10. Prospective validation is done before the production and during the development stage. In prospective validation one has to draw up the plans and has to do the risk analysis. The primary aim is to establish the controlled synergy. 1. Prospective validation:

11. To define commercial production process To define CQA (Critical Quality Attributes) and CPP (Critical Process Parameter) Risk assessment – FMEA (Failure Mode And Effect Analysis) Control to mitigate risk Objectives of prospective validation :

12. Concurrent validation is done to assure and demonstrate that the process will remain in state of control during commercial manufacturing. 2. CONCURRENT VALIDATION :

13. Qualification of process designed in stage-1 Commercial scale production batches Close monitoring of all process parameters Insight on variability and our current controls Design of facility and qualification of equipment Concurrent validation is done for:

14. In this validation one has to collect and evaluate information and data about : -performance of the process. -final control tests. How well the process parameters remain to the acceptable range Data should be assessed periodically. 3. Retrospective validation :

15. In retrospective validation the evaluation parameters includes : 1. Relevant Process Trends 2. Quality of incoming materials 3. In Process Material ,Etc. Data generated is statistically trended and reviewed by trained person. Retrospective validation:

16. Why revalidation is required ? When any changes are made in the process or its environment it is very essential to ensure that it should not any adverse effect on : - Product Quality or - Process Characteristics 4. Revalidation:

17. Changes in starting material Changes in packaging material Changes in process Changes in equipment Changes in support system or production area When revalidation is required:

18. a. Change in starting material:

19. b. Change in packaging material:

20. c. Changes in process :

21. d. Change in equipment:

22. e. Change in support system or production area

23. Different Types of Validation Parameters : Accuracy. Precision . Specificity . Linearity . Range . Limit of Detection. Limit of Quantification. Ruggedness . Robustness . 5. VALIDATION PARAMETERS :

24. Accuracy : Definition : It is the closeness of agreement between the actual value and measured value. Accuracy is calculated as the percentage of recovery by the assay of the known added amount of the analyte in the sample or the difference between the mean and accepted true value together with confidence intervals. The ICH guidance recommended to take a minimum of 3 concentration levels covering the specified range and 3 replicates of each concentration are analyzed (totally 3 * 3 = 9 determination) 5 . VALIDATION PARAMETERS :

25. Precision: Definition : The closeness of agreement between a series of measurements multiple samplings of the same homogeneous sample under prescribed condition. The precision of test method is usually expressed as the standard deviation or relative standard deviation of a series of measurements. Precision may be considered at three levels: Repeatability , Intermediate Precision and reproducibility. 5 . VALIDATION PARAMETERS :

26. Method precision (Repeatability): Repeatability expresses the precision under the same operating conditions over a short interval of time. repeatability is also termed intra-assay precision. Intermediate Precision: It expresses with in laboratory variations; different days, different analysts, different equipment, etc. Reproducibility: Precision between laboratories (mostly performed during analytical method transfer). 5 . VALIDATION PARAMETERS :

27. Relative standard deviation: This serves as a daily evaluation of the repeatability of the system. Often, the relative standard deviation calculated as % RSD for five or six replicate injections of a reference standard or working standard is measured at the beginning of each set of analyses. Standard deviation is calculated using the formula Where, s = standard deviation x = each value in the sample æ= mean of the values N = the no. of values ( sample size) 5 . VALIDATION PARAMETERS :

28. Specificity : Definition The ability to assess unequivocally the analyte in the presence of components that may be expected to present, such as impurities, degradation products and matrix components, etc. Methodology : Specificity shall be demonstrated by performing Placebo / blank interference and forced degradation studies. Blank interference: Prepare blank solutions as per the test method and analyze them as per the test method. 5 . VALIDATION PARAMETERS :

29. 2. Placebo interference (In case of Drug products): Prepare the placebo solution equivalent to the test concentration (Subtract the weight of active ingredient) and analyze it as per the test method. 3 . Force Degradation studies : Degrade the sample forcefully under the various stress conditions like Light, heat, humidity, acid/base/water hydrolysis, and oxidation and ensure the degradation and for peak purity. Note : Based on the physicochemical properties and literature stress conditions can be decided. 5 . VALIDATION PARAMETERS :

30. Linearity and Range : Linearity: The linearity of an analytical procedure is its ability (within a given range) to obtain test results which are directly proportional to the concentration (amount) of analyte in the sample. Range: The range of analytical procedure is the interval between the upper and lower concentrations of analyte in the analytical procedure has a suitable level of precision, accuracy, and linearity. 5 . VALIDATION PARAMETERS :

31. Methodology: At least 6 replicates per concentrations to be studied. Plot a graph of concentration (on the x-axis) Vs mean response (on Y-axis). Calculate the regression equation, Y – intercept and correlation coefficient. Linearity shall be established across the range. If linearity is not meeting the acceptance criteria, establish the range of concentration in which it is linear. 5 . VALIDATION PARAMETERS :

32. Correlation Co-efficient : A measure of the strength of linear association between two variables. The correlation will always between -1.0 and +1.0. If the correlation is positive, we have a positive relationship. If it is negative, the relationship is negative . Where, N = Number of values or elements X = First Score Y = Second Score Σxy = Sum of the product of first and Second Scores Σx = Sum of First Scores Σy = Sum of Second Scores Σx 2 = Sum of square First Scores Σy 2 = Sum of square Second Scores 5 . VALIDATION PARAMETERS :

33. Limit of Detection : Definition: It is the lowest amount of analyte in a sample that can be detected but not necessarily quantified under the stated experimental conditions. Methodology : Visual Evaluation Method: The visual evaluation may be used for non-instrumental methods but may also be used with instrumental methods. The detection limit is determined by the analysis of samples with known concentrations of analyte and by establishing the minimum level at which the analyte can be reliably detected. 5 . VALIDATION PARAMETERS :

34. Based on Signal to Noise Ratio Method: This approach can only be applied to analytical procedures which exhibit baseline noise. Determination of the signal to-noise ratio is performed by comparing measured signals from samples with known low concentrations of analyte with those of blank samples and establishing the minimum concentration at which the analyte can be reliably detected. A signal-to-noise ratio between 3 or 2:1 is generally considered acceptable for estimating the detection limit . Based on the standard Deviation of the Response and the Slope: The detection limit (DL) may be expressed as: The formula for calculating LOD is LOD = 3.3 δ/S Where δ = standard deviation of intercepts of calibration curves. S = the slope of the linearity plot. The slope shall be estimated from the calibration curve of the analyte. 5 . VALIDATION PARAMETERS :

35. Based on the Standard Deviation of the Blank: Measurement of the magnitude of analytical background response is performed by analyzing an appropriate number of blank samples and calculating the standard deviation of these responses. Based on the Calibration Curve: A specific calibration curve should be studied using samples containing an analyte in the range of DL. The residual standard deviation of a regression line or the standard deviation of y-intercepts of regression lines may be used as the standard deviation. 5 . VALIDATION PARAMETERS :

36. Limit of Quantification : Definition : It is lowest amount of analyte in a sample, which can be quantitatively determined with acceptable accuracy and precision. Methodology : Following are different approaches: Visual evaluation method: The visual evaluation may be used for non-instrumental methods but may also be used with instrumental methods. The quantitation limit is generally determined by the analysis of samples with known concentrations of analyte and by establishing the minimum level at which the analyte can be quantified with acceptable accuracy and precision. 5 . VALIDATION PARAMETERS :

37. Based on signal to noise ratio method: This approach can only be applied to analytical procedures that exhibit baseline noise. Determination of the signal-to-noise ratio is performed by comparing measured signals from samples with known low concentrations of analyte with those of blank samples and by establishing the minimum concentration at which the analyte can be reliably quantified. A typical signal-to-noise ratio is 10:1 . Based on the standard Deviation of the Response and the Slope: The formula for calculating LOQ is LOQ = 10 δ/S Where δ = standard deviation of response. S = Mean of slopes of the calibration curves . 5 . VALIDATION PARAMETERS :

38. Based on the Standard Deviation of the Blank Measurement of the magnitude of analytical background response is performed by analyzing an appropriate number of blank samples and calculating the standard deviation of these responses. Based on the Calibration Curve A specific calibration curve should be studied using samples, containing an analyte in the range of QL. The residual standard deviation of a regression line or the standard deviation of y-intercepts of regression lines may be used as the standard deviation. 5 . VALIDATION PARAMETERS :

39. Ruggedness Definition : Ruggedness is the degree of reproducibility of test results obtained by the analysis of the same samples under a variety of test conditions such as different laboratories, analysis, instruments, reagent lots, elapsed assay times, temperature, days, etc. It can be expressed as a lack influence of the operation and environmental variable on the test results of the analytical method. 5 . VALIDATION PARAMETERS :

40. Robustness Definition : It is a measure of the method's ability to remain unaffected by small but deliberate variations in method parameters and provides an indication of its reliability during normal usage. If measurements are susceptible to variations in analytical conditions, the analytical conditions should be suitably controlled or a precautionary statement should be included in the procedure. 5 . VALIDATION PARAMETERS :

41. Examples of typical variations are: Stability of analytical solutions Extraction time In the case of liquid chromatography, examples of typical variations are: Influence of variations of ph in a mobile phase Influence of variations in mobile phase composition Different columns (different lots and/or suppliers) Temperature Flow rate 5 . VALIDATION PARAMETERS :

42. The following are the typical method parameters need to change deliberately and verify during method validation : Flow rate: (+/- 0.2ml/minutes). Mobile phase composition: (+/- 10% of organic phase). Column oven temperature: (+/- 5°C). PH of buffer in mobile phase: (+/- 0.2 units). Filter suitability: (At least two filters). 5 . VALIDATION PARAMETERS :

43. Methodology: Mobile phase variation: Prepare the mobile phases by changing organic phase to +/-10 % of the mobile phase composition. Flow rate: Change the flow rate by +/- 0.2 ml/minutes of the target flow rate mentioned in test method. Temperature of the Column: Change the temperature of the column by +/- 5.0°C of the target temperature mentioned in Test method. PH of the buffer of mobile phase: Prepare the mobile phases by changing the pH of the buffer by +/- 0.2 units of the pH mentioned in the test method. Filter Suitability: Prepare the test solution as per the test method and filter through two different types of filters. Analyse the sample as per the test method and compare the results against the unfiltered / centrifuged sample. 5 . VALIDATION PARAMETERS :

44. Prabh Simran Singh, Gagan Shah, Analytical Method Development and Validation, Journal of Pharmacy Research, 4(7 ), 2011, 2330-2332 . Ravisankar P, Gowthami S, and Devala Rao G, A review on analytical method development, Indian journal of research in pharmacy and biotechnology, 2, 2014, 1183-1195 . Validation of analytical procedure: Methodology Q2B, ICH Harmonized Tripartite Guidelines, 1996:1-8 . International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use ICH Harmonized tripartite guideline Validation Ravisankar P, Anusha S, Supriya K, Ajith Kumar U, Fundamental chromatographic parameters, Int. J. Pharm. Sci . Rev. Res., 55(2), 2019,46-50. REFERENCES